The CEO of Nvidia, Jensen Huang, predicts that the shortage of entry-level developers will ease by 2028, as new graduates trained in artificial intelligence (AI) begin entering the workforce. These graduates will bring skills in working with AI systems, which are expected to assist in automating basic coding tasks. This shift could change how developers are trained, as AI tools may take over routine aspects of programming. Companies are being advised to create secure testing environments and ensure AI agents are reliable in real-world settings. For many years, the tech industry has followed a standard model where new graduates started with entry-level roles such as bug fixing, software testing, and documentation. These jobs provided a foundation for learning complex systems and developing professional skills. However, this model is now being challenged by the rapid rise of AI, which can perform many of these tasks more quickly and efficiently than humans. Testimonies from around the world suggest that junior engineers are facing fewer opportunities as AI tools take over tasks that were once the domain of beginners. These tools can generate code, detect errors, and even fix problems in seconds. A 2025 report found that major tech companies have hired over 50% fewer young graduates in the past three years. Huang had previously warned in 2024 that learning to program might become less relevant, as AI could handle many details of projects automatically. Despite these concerns, Huang does not believe AI will eliminate software engineering jobs. Instead, he sees AI as a new layer of abstraction, similar to tools like calculators and personal computers. He predicts that future engineers will need to work closely with AI systems. Huang also believes that this shift will lead to a new generation of engineers who can think more broadly about systems, even if some basic coding knowledge may fade. He argues that the core of software engineering—problem-solving and design—will remain important, even as AI handles more routine tasks. The Bureau of Labor Statistics (BLS) reported in May that 18 professions have seen job losses due to AI, affecting around 10 million jobs in the U.S. However, software development is not among them, and demand for software developers is expected to grow as AI expands. AI is likely to take over many entry-level tasks, such as debugging and testing, which raises questions about how junior developers will learn to evaluate AI-generated code. Studies show a growing gap in hiring for young people in AI-related fields. Technology companies are increasingly integrating AI into their workflows from the start. Employees are monitored on how they use AI during evaluations, and those who resist may face consequences. Entry-level roles are being phased out in favor of AI-assisted positions. However, this shift may lead to a focus on surface-level skills rather than deep understanding. Huang has emphasized the need for strong safeguards for AI systems, comparing them to virtual machines used for testing software. He also noted that Nvidia is heavily focused on verifying AI outputs, with 80% of engineering efforts going toward this task. As AI takes on more coding responsibilities, developers may spend more time ensuring that AI-generated code works within set boundaries. Managers are advised to update hiring and training programs to include AI collaboration, while development teams should focus on helping junior engineers build judgment in an increasingly automated environment. Companies are also encouraged to invest in secure testing environments and monitoring systems for AI in production. Huang has told Nvidia’s engineers that those who don’t use AI tools widely are not as productive, as AI can now assist in intellectual tasks, allowing engineers to focus on more creative work.